{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bike Sharing Dataset Exploratory Analysis\n",
    "\n",
    "+ Based on Bike Sharing dataset from [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset)\n",
    "+ This notebook is based upon the hourly data file, i.e. hour.csv\n",
    "\n",
    "---\n",
    "Reference:\n",
    "Fanaee-T, Hadi, and Gama, Joao, 'Event labeling combining ensemble detectors and background knowledge', Progress in Artificial Intelligence (2013): pp. 1-15, Springer Berlin Heidelberg,"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import required packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# data manipulation \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# plotting\n",
    "import seaborn as sn\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "# setting params\n",
    "params = {'legend.fontsize': 'x-large',\n",
    "          'figure.figsize': (30, 10),\n",
    "          'axes.labelsize': 'x-large',\n",
    "          'axes.titlesize':'x-large',\n",
    "          'xtick.labelsize':'x-large',\n",
    "          'ytick.labelsize':'x-large'}\n",
    "\n",
    "sn.set_style('whitegrid')\n",
    "sn.set_context('talk')\n",
    "\n",
    "plt.rcParams.update(params)\n",
    "pd.options.display.max_colwidth = 600\n",
    "\n",
    "# pandas display data frames as tables\n",
    "from IPython.display import display, HTML"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Shape of dataset::(17379, 17)\n"
     ]
    }
   ],
   "source": [
    "hour_df = pd.read_csv('hour.csv')\n",
    "print(\"Shape of dataset::{}\".format(hour_df.shape))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>dteday</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.81</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>13</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8</td>\n",
       "      <td>32</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.22</td>\n",
       "      <td>0.2727</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5</td>\n",
       "      <td>27</td>\n",
       "      <td>32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>10</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0.24</td>\n",
       "      <td>0.2879</td>\n",
       "      <td>0.75</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   instant      dteday  season  yr  mnth  hr  holiday  weekday  workingday  \\\n",
       "0        1  2011-01-01       1   0     1   0        0        6           0   \n",
       "1        2  2011-01-01       1   0     1   1        0        6           0   \n",
       "2        3  2011-01-01       1   0     1   2        0        6           0   \n",
       "3        4  2011-01-01       1   0     1   3        0        6           0   \n",
       "4        5  2011-01-01       1   0     1   4        0        6           0   \n",
       "\n",
       "   weathersit  temp   atemp   hum  windspeed  casual  registered  cnt  \n",
       "0           1  0.24  0.2879  0.81        0.0       3          13   16  \n",
       "1           1  0.22  0.2727  0.80        0.0       8          32   40  \n",
       "2           1  0.22  0.2727  0.80        0.0       5          27   32  \n",
       "3           1  0.24  0.2879  0.75        0.0       3          10   13  \n",
       "4           1  0.24  0.2879  0.75        0.0       0           1    1  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(hour_df.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Types and Summary Stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "instant         int64\n",
       "dteday         object\n",
       "season          int64\n",
       "yr              int64\n",
       "mnth            int64\n",
       "hr              int64\n",
       "holiday         int64\n",
       "weekday         int64\n",
       "workingday      int64\n",
       "weathersit      int64\n",
       "temp          float64\n",
       "atemp         float64\n",
       "hum           float64\n",
       "windspeed     float64\n",
       "casual          int64\n",
       "registered      int64\n",
       "cnt             int64\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# data types of attributes\n",
    "hour_df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>instant</th>\n",
       "      <th>season</th>\n",
       "      <th>yr</th>\n",
       "      <th>mnth</th>\n",
       "      <th>hr</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>17379.0000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "      <td>17379.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>8690.0000</td>\n",
       "      <td>2.501640</td>\n",
       "      <td>0.502561</td>\n",
       "      <td>6.537775</td>\n",
       "      <td>11.546752</td>\n",
       "      <td>0.028770</td>\n",
       "      <td>3.003683</td>\n",
       "      <td>0.682721</td>\n",
       "      <td>1.425283</td>\n",
       "      <td>0.496987</td>\n",
       "      <td>0.475775</td>\n",
       "      <td>0.627229</td>\n",
       "      <td>0.190098</td>\n",
       "      <td>35.676218</td>\n",
       "      <td>153.786869</td>\n",
       "      <td>189.463088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>5017.0295</td>\n",
       "      <td>1.106918</td>\n",
       "      <td>0.500008</td>\n",
       "      <td>3.438776</td>\n",
       "      <td>6.914405</td>\n",
       "      <td>0.167165</td>\n",
       "      <td>2.005771</td>\n",
       "      <td>0.465431</td>\n",
       "      <td>0.639357</td>\n",
       "      <td>0.192556</td>\n",
       "      <td>0.171850</td>\n",
       "      <td>0.192930</td>\n",
       "      <td>0.122340</td>\n",
       "      <td>49.305030</td>\n",
       "      <td>151.357286</td>\n",
       "      <td>181.387599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.0000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.020000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>4345.5000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.340000</td>\n",
       "      <td>0.333300</td>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.104500</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>40.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>8690.0000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.484800</td>\n",
       "      <td>0.630000</td>\n",
       "      <td>0.194000</td>\n",
       "      <td>17.000000</td>\n",
       "      <td>115.000000</td>\n",
       "      <td>142.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>13034.5000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>18.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.660000</td>\n",
       "      <td>0.621200</td>\n",
       "      <td>0.780000</td>\n",
       "      <td>0.253700</td>\n",
       "      <td>48.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>281.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17379.0000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.850700</td>\n",
       "      <td>367.000000</td>\n",
       "      <td>886.000000</td>\n",
       "      <td>977.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          instant        season            yr          mnth            hr  \\\n",
       "count  17379.0000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean    8690.0000      2.501640      0.502561      6.537775     11.546752   \n",
       "std     5017.0295      1.106918      0.500008      3.438776      6.914405   \n",
       "min        1.0000      1.000000      0.000000      1.000000      0.000000   \n",
       "25%     4345.5000      2.000000      0.000000      4.000000      6.000000   \n",
       "50%     8690.0000      3.000000      1.000000      7.000000     12.000000   \n",
       "75%    13034.5000      3.000000      1.000000     10.000000     18.000000   \n",
       "max    17379.0000      4.000000      1.000000     12.000000     23.000000   \n",
       "\n",
       "            holiday       weekday    workingday    weathersit          temp  \\\n",
       "count  17379.000000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean       0.028770      3.003683      0.682721      1.425283      0.496987   \n",
       "std        0.167165      2.005771      0.465431      0.639357      0.192556   \n",
       "min        0.000000      0.000000      0.000000      1.000000      0.020000   \n",
       "25%        0.000000      1.000000      0.000000      1.000000      0.340000   \n",
       "50%        0.000000      3.000000      1.000000      1.000000      0.500000   \n",
       "75%        0.000000      5.000000      1.000000      2.000000      0.660000   \n",
       "max        1.000000      6.000000      1.000000      4.000000      1.000000   \n",
       "\n",
       "              atemp           hum     windspeed        casual    registered  \\\n",
       "count  17379.000000  17379.000000  17379.000000  17379.000000  17379.000000   \n",
       "mean       0.475775      0.627229      0.190098     35.676218    153.786869   \n",
       "std        0.171850      0.192930      0.122340     49.305030    151.357286   \n",
       "min        0.000000      0.000000      0.000000      0.000000      0.000000   \n",
       "25%        0.333300      0.480000      0.104500      4.000000     34.000000   \n",
       "50%        0.484800      0.630000      0.194000     17.000000    115.000000   \n",
       "75%        0.621200      0.780000      0.253700     48.000000    220.000000   \n",
       "max        1.000000      1.000000      0.850700    367.000000    886.000000   \n",
       "\n",
       "                cnt  \n",
       "count  17379.000000  \n",
       "mean     189.463088  \n",
       "std      181.387599  \n",
       "min        1.000000  \n",
       "25%       40.000000  \n",
       "50%      142.000000  \n",
       "75%      281.000000  \n",
       "max      977.000000  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dataset summary stats\n",
    "hour_df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The dataset has:\n",
    "+ 17 attributes in total and 17k+ records\n",
    "+ Except dtedat, rest all are numeric(int or float)\n",
    "+ As stated on the UCI dataset page, the following attributes have been normalized (same is confirmed above):\n",
    "    + temp, atemp\n",
    "    + humidity\n",
    "    + windspeed\n",
    "+ Dataset has many categorical variables like season, yr, holiday, weathersit and so on. These will need to handled with care"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Standardize Attribute Names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "hour_df.rename(columns={'instant':'rec_id',\n",
    "                      'dteday':'datetime',\n",
    "                      'holiday':'is_holiday',\n",
    "                      'workingday':'is_workingday',\n",
    "                      'weathersit':'weather_condition',\n",
    "                      'hum':'humidity',\n",
    "                      'mnth':'month',\n",
    "                      'cnt':'total_count',\n",
    "                      'hr':'hour',\n",
    "                      'yr':'year'},inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Typecast Attributes "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# date time conversion\n",
    "hour_df['datetime'] = pd.to_datetime(hour_df.datetime)\n",
    "\n",
    "# categorical variables\n",
    "hour_df['season'] = hour_df.season.astype('category')\n",
    "hour_df['is_holiday'] = hour_df.is_holiday.astype('category')\n",
    "hour_df['weekday'] = hour_df.weekday.astype('category')\n",
    "hour_df['weather_condition'] = hour_df.weather_condition.astype('category')\n",
    "hour_df['is_workingday'] = hour_df.is_workingday.astype('category')\n",
    "hour_df['month'] = hour_df.month.astype('category')\n",
    "hour_df['year'] = hour_df.year.astype('category')\n",
    "hour_df['hour'] = hour_df.hour.astype('category')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize Attributes, Trends and Relationships"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Hourly distribution of Total Counts\n",
    "+ Seasons are encoded as 1:spring, 2:summer, 3:fall, 4:winter\n",
    "+ Exercise: Convert season names to readable strings and visualize data again"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Season wise hourly distribution of counts')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=hour_df[['hour',\n",
    "                           'total_count',\n",
    "                           'season']],\n",
    "             x='hour',y='total_count',\n",
    "             hue='season',ax=ax)\n",
    "ax.set(title=\"Season wise hourly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ The above plot shows peaks around 8am and 5pm (office hours)\n",
    "+ Overall higher usage in the second half of the day"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Weekday wise hourly distribution of counts')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.pointplot(data=hour_df[['hour','total_count','weekday']],x='hour',y='total_count',hue='weekday',ax=ax)\n",
    "ax.set(title=\"Weekday wise hourly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Weekends (0 and 6) and Weekdays (1-5) show different usage trends with weekend's peak usage in during afternoon hours\n",
    "+ Weekdays follow the overall trend, similar to one visualized in the previous plot\n",
    "+ Weekdays have higher usage as compared to weekends\n",
    "+ It would be interesting to see the trends for casual and registered users separately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Box Pot for hourly distribution of counts')]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.boxplot(data=hour_df[['hour','total_count']],x=\"hour\",y=\"total_count\",ax=ax)\n",
    "ax.set(title=\"Box Pot for hourly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Early hours (0-4) and late nights (21-23) have low counts but significant outliers\n",
    "+ Afternoon hours also have outliers\n",
    "+ Peak hours have higher medians and overall counts with virtually no outliers"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Monthly distribution of Total Counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Monthly distribution of counts')]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots()\n",
    "sn.barplot(data=hour_df[['month',\n",
    "                         'total_count']],\n",
    "           x=\"month\",y=\"total_count\")\n",
    "ax.set(title=\"Monthly distribution of counts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Months June-Oct have highest counts. Fall seems to be favorite time of the year to use cycles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0.5, 1.0, 'Winter')]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_col_list = ['month','weekday','total_count']\n",
    "plot_col_list= ['month','total_count']\n",
    "spring_df = hour_df[hour_df.season==1][df_col_list]\n",
    "summer_df = hour_df[hour_df.season==2][df_col_list]\n",
    "fall_df = hour_df[hour_df.season==3][df_col_list]\n",
    "winter_df = hour_df[hour_df.season==4][df_col_list]\n",
    "\n",
    "fig,ax= plt.subplots(nrows=2,ncols=2)\n",
    "sn.barplot(data=spring_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[0][0],)\n",
    "ax[0][0].set(title=\"Spring\")\n",
    "\n",
    "sn.barplot(data=summer_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[0][1])\n",
    "ax[0][1].set(title=\"Summer\")\n",
    "\n",
    "sn.barplot(data=fall_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[1][0])\n",
    "ax[1][0].set(title=\"Fall\")\n",
    "\n",
    "sn.barplot(data=winter_df[plot_col_list],x=\"month\",y=\"total_count\",ax=ax[1][1])  \n",
    "ax[1][1].set(title=\"Winter\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Year Wise Count Distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fb123ddb7b8>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sn.violinplot(data=hour_df[['year',\n",
    "                            'total_count']],\n",
    "              x=\"year\",y=\"total_count\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Both years have multimodal distributions\n",
    "+ 2011 has lower counts overall with a lower median\n",
    "+ 2012 has a higher max count though the peaks are around 100 and 300 which is then tapering off"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Working Day Vs Holiday Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20ae6a90a90>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UGouyzRk5cuQWrSsWi3n11VeTJGPHjs1+++2X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\nAAAAAACAtqLkO9/WmTlzZhYuXJgPP/xwve0NDQ1ZvXp1lix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      "text/plain": [
       "<matplotlib.figure.Figure at 0x20ae6bfe048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2) = plt.subplots(ncols=2)\n",
    "sn.barplot(data=hour_df,x='is_holiday',y='total_count',hue='season',ax=ax1)\n",
    "sn.barplot(data=hour_df,x='is_workingday',y='total_count',hue='season',ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Outliers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20ae70879b0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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33XXXYqFQaHZ/eNq0acXa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\nqEuXmJ5T4TEAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x20ae65e9c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,(ax1,ax2)= plt.subplots(ncols=2)\n",
    "sn.boxplot(data=hour_df[['total_count',\n",
    "                         'casual','registered']],ax=ax1)\n",
    "sn.boxplot(data=hour_df[['temp','windspeed']],ax=ax2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Correlations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x20ae70b0048>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PPZobfUpDtq5UMXe3DK+1sbNTh6kjNP1SkGbfPaEhW1eqrEeNVNfkK+aift/M1We3f5P/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\n9Ir/A9JbuUbAHiRjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x20ae7196e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "corrMatt = hour_df[[\"temp\",\"atemp\",\n",
    "                    \"humidity\",\"windspeed\",\n",
    "                    \"casual\",\"registered\",\n",
    "                    \"total_count\"]].corr()\n",
    "mask = np.array(corrMatt)\n",
    "mask[np.tril_indices_from(mask)] = False\n",
    "sn.heatmap(corrMatt, mask=mask,\n",
    "           vmax=.8, square=True,annot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "+ Correlation between temp and atemp is very high (as expected)\n",
    "+ Same is te case with registered-total_count and casual-total_count\n",
    "+ Windspeed to humidity has negative correlation\n",
    "+ Overall correlational statistics are not very high."
   ]
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
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